Thesis
Dynamic analysis of raising sunken vessels using buoyant systems
- Creator
- Rights statement
- Awarding institution
- University of Strathclyde
- Date of award
- 2014
- Thesis identifier
- T13807
- Qualification Level
- Qualification Name
- Department, School or Faculty
- Abstract
- In this research, mathematical formulations for the dynamics of raising sunken vessels using buoyant systems are developed in a form which is suitable for integrating control techniques to ensure both hydrodynamic and structural stability for a safe and stable salvaging operation based on both rigid body modeling and flexible body modeling concepts. Due to the coupled nature of salvage dynamics and for integrating controller techniques, the mathematical modeling is carried out as two subsystems. In the primary model, the salvage dynamics is formulated in such a way that the variation in additional buoyancy due to flow rate of filling gas inside the lift bags is the controlling force with respect to hydrostatic force due to weight, buoyancy and suction break out, hydrodynamic forces and uncertainty arises due to any external disturbances. In the secondary model, the purging of gas through the valves is taken as the control parameter by accounting the excess buoyancy available after suction break out and to the variation in pressure difference between gas inside lift bag and surrounding sea water pressure for a stable ascent. According to the simplified two-degree-of-freedom equations of rigid-body vessel motion, a state space model is developed for integrating the primary controller. Initially a proportional derivative (PD) controller is selected as the primary controller for regulating the flow rate of filling gas inside the lift bags according to the buoyancy requirement and extended to other classic controllers like proportional integral and derivative (PID) controller and sliding mode controller (SMC) for improving the performance. Numerical simulations are carried out in MATLAB & SIMULINK by solving the standard State Dependent Ricatti Equation in a body-fixed coordinate reference frame. Preliminary results in terms of coordinate positions or trajectories, linear and angular velocity components of the raising body are evaluated based on an experimental pontoon model. A number of case studies are carried out for different target depths with the developed linear state space model including sensitivity analysis such as change in hydrodynamic coefficients, breakout lift force and the effect of external disturbances and uncertainty. SMC is found to be the optimum choice among these conventional controllers by satisfying the Lyapunov stability condition even for higher water depths with system robustness and capability to handle parameter variations, external disturbances and uncertainty. The tuning effort and chattering were found to be the two major draw backs of conventional sliding mode controller (CSMC), which is improved by integrating it with artificial intelligence such as fuzzy logic controller to bring together the advantages of both controllers to become fuzzy sliding mode controllers (FSMCs).;In FSMCs, the performance of the CSMC is improved by dynamically computing the sliding surface slope by a FLC and adaptively computing the controller gain by another FLC. FLCs are designed using MATLAB's fuzzy logic interface based on Mamdani's implification method the combined models will be developed in SIMULINK. A two input fuzzy sliding mode controller (TIFSMC) is designed first and later simplified to single input fuzzy sliding mode controller (SIFSMC), for reducing the tuning effort and computational time. With the development of SIFSMC, the tuning process becomes standardized and hassle free and hence the well known chattering problem associated with SMCs is avoided. The comparative performance of the fuzzy sliding mode controllers over CSMC has been investigated by performing numerical simulations on the pontoon model. It is found that both FSMCs show 30% of improvement in the tracking performance when compared to the CSMC, while maintaining its robustness. It is also noted that FSMCs are less sensitive to external disturbances and uncertainties in comparison with CSMC. The responses obtained by the SIFSMC are the same as those obtained by the TIFSMC, with the former involving a much less tuning effort and computational time. Simulation studies reveals the fact that for complicated non linear underwater operations like marine salvage involving uncertainty and external disturbances, a closed loop control system is mandatory and an adaptive controller like SIFSMC is the optimum choice as the primary controller for regulating the gas flow rate. Purge valve modeling is carried out according to the excess buoyancy available after suction breakout and to the variation in pressure difference between gas inside the lift bags and surrounding sea water for a stable ascent. A PID controller is designed as the secondary controller for regulating the purging of gas through the valves and found to be effective in maintaining the ascent velocity within the stable region. Then a supervisory fuzzy logic controller is designed to monitor or switch between the primary and secondary controllers based on the buoyancy requirement for a safe and stable salvaging operation. The Gaussian membership functions are used for representing input and output variables, and the centroid method is used for defuzzification. Using a trial and error approach, the best inference mechanism to use in this case seems to be the prod-probor method. Because of simplicity and availability of the graphical user interface (GUI) in MATLAB, Mamdani inference engine is employed for designing the FLC that uses minimum operator for a fuzzy implication and max-min operator for composition The defuzzification technique used is found using trial and error and Centre of Gravity approach is the one which provides least integral square error. From the simulation studies, it is found that FLC is capable to maintain hydrodynamic stability in diving plane by suitably defining the linguistic fuzzy rules, which are created based on the author's experience in conducting numerical simulation using primary and secondary controllers.;Finally, in order to find the optimum location of lift bags on the vessel and to determine the controlled response of individual lift bags or the real case of lifting a very flexible structure, such as a long pipe, using multiple controlled lift bags, the problem is extended to a detailed flexible body modeling and control. In this regard, a chemical tanker is taken and modeled as an elastic Euler-Bernoulli beam with free-free boundary conditions. Free vibration analysis is carried out on the model via an analytical as well as finite element method, and the obtained responses such as natural frequencies and mode shapes are evaluated and compared. From the mode shape plots, the lift bags are located suitably on the "nodes of a mode" of the beam, where the displacement is negligible. Then the eigenvectors are normalized with respect to mass, and the equation of motion is developed in principal coordinates after defining the nodal forces and moments. Then the modal contributions of individual modes are analyzed according to their dc gain/peak gain value to define, which ones have greatest contribution and later several modal reduction techniques such as 'modred-mdc' and 'modred-del' are used to obtain the smallest state space models for individual lift bags that represents the pertinent system dynamics. Highest dc gain is obtained for the first two rigid modes, which implies that rigid body modes are more significant compared to flexible modes for the control of lifting during marine salvage. However flexible modes relate to structural hull girder moments which should also be considered. Preliminary results in terms of coordinate positions or trajectories, linear and angular velocity components of the raising body at various sections of the vessel or beam nodes can be estimated. Longitudinal distribution of shear force and bending moments across the tanker are also evaluated. The full and reduced order modal responses for lift bags are compared in both frequency and time domains. It is observed that 'unsorted modred-mdc' is the preferred choice for modal order reduction compared to other modal reduction methods. Using a flexible body modeling approach the state space model is available for individual nodes on the beam. Thus controlled response of individual lift bags can be simulated. This is an advantage of flexible body modeling & control over rigid body modeling & control. Finally a supervisory fuzzy logic controller is integrated with the 4*4 flexible state space model obtained using 'unsorted modred-mdc' to obtain the controlled stable responses of individual external lift bags.
- Resource Type
- DOI
- Date Created
- 2014
- Former identifier
- 1038267
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